Usage of Big Data Technology in Controlling

Rybicka, Karolina

doi:10.5430/rwe.v10n4p92

Cited by 5 publications

(11 citation statements)

References 12 publications

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“…With the continuous development of the electronic information industry, big data technology has also played a great role in all walks of life [1,2]. It not only changes the way people live and learn, but also updates people's thinking constantly.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Ideological and Political Education Management Strategies under k-Means Algorithm in Big Data Environment

Wang

2022

Security and Communication Networks

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The development of information technology has promoted the reform of ideological and political education in colleges and universities. A large amount of data has been accumulated in the education management database, and the information implied by these data can provide scientific guidance for the optimization of educational management strategies in colleges and universities. The relationship and characteristics of big data in ideological and political education in colleges and universities were expounded, and the feasibility of applying big data technology to ideological and political education was analyzed. The k-means algorithm was selected for cluster analysis, and its process and principles were expounded. As the traditional k-means clustering algorithm has low data processing efficiency and large deviation of the results, the algorithm was optimized by controlling the iterative method of the algorithm. Besides, the ideological and political education management under the optimized k-means algorithm was established. The work assessment quantitative scale in the management of ideological and political education was adopted as the data source, and the optimized k-means algorithm was used to carry out cluster analysis. The results show that management attitude was scored as 0.634, the management ability was 0.6092, the management effect was 0.6082, and the management method was 0.5792. It was indicated that all the scores were above the middle for greater than 0.5, suggesting that the overall management level was above the middle, which was relatively good. The optimized k-means-based ideological and political education management strategy model can analyze the current educational management status of colleges and universities more accurately. It can also provide scientific guidance for colleges and universities to conduct teaching management reasonably and scientifically according to the data analysis results. The optimized k-means algorithm was compared with the traditional algorithm, from which the optimized algorithm was obviously better than the traditional algorithm in terms of clustering effect and operation stability.

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Section: Introductionmentioning

confidence: 99%

Optimization of Ideological and Political Education Management Strategies under k-Means Algorithm in Big Data Environment

Wang

2022

Security and Communication Networks

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“…Cloud computing enables scalable data storage and processing, facilitating real-time analytics (Ren, 2022). Meanwhile, machine learning algorithms enhance predictive analytics, allowing for more accurate forecasting and risk assessment (Rybicka, 2019). This evolution is marked by the increasing integration of data analytics into financial decisionmaking processes, improving efficiency and strategic planning (Müller et al, 2018;Shamim et al, 2020).…”

Section: Big Data In Financial Managementmentioning

confidence: 99%

“…Streamlining financial reporting processes through automated data collection and analysis reduces the time and effort required to produce accurate financial statements (Popoviăź et al, 2016). Moreover, big data analytics enhances fraud detection and prevention by identifying unusual patterns and anomalies in financial transactions, thereby mitigating the risk of financial fraud (Ren, 2022;Rybicka, 2019). Enhanced risk management capabilities, including early warning systems for financial risks, credit risk assessment, and regulatory compliance, further underscore the transformative impact of big data on financial management (Trigo et al, 2016;Zhou & Li, 2017).…”

Section: Academic Journal On Business Administration Innovation and S...mentioning

confidence: 99%

Untitled

2024

AJBAIS

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“…It is not easy to comprehensively promote the application of big data in financial management decisions. In reality, there are many obstacles, such as outdated concepts of financial managers, refusal to innovate, poor internal information sharing, poor financial risk awareness, weak control ability, and insufficient control ability of financial information technology personnel [2]. It is not easy to comprehensively promote the application of big data in financial management decision-making.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Enterprise Financial Management and Decision‐Making Systems Based on Big Data

Ren

2022

Journal of Mathematics

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Based on information asymmetry theory, principal-agent theory, and risk management theory, this paper analyzes the mechanism of the impact of big data on financial decision-making, analyzing four dimensions: how big data enhances the information base for forecasting, how big data improves the relevance of decision-making, how big data builds new competitive advantages, and how big data promotes dynamic decision-making. Secondly, through the analysis of specific implementation cases of enterprise big data in financial decision-making, we focus on the real problems faced in management and the effect of solving problems through big data platform. The enterprise realizing the integration of business and finance not only can better lead business expansion, but also can improve the management level within the enterprise, which is conducive to the improvement of core competitiveness. The integration of industry and finance is essentially achieved through the application of various financial management modules to the business operations of enterprises, including budget management, capital management, fixed asset management, and financial accounting. If we want to implement the whole process of financial integration, it is impossible to achieve this manually, and we must first build a powerful information system as a guarantee. Under the guidance of theories of information asymmetry, stakeholders, and management information systems, Internet finance enterprises should build their own integrated business finance system based on the demand for business finance integration in the Internet finance industry, to enhance the matching of business finance data of Internet finance enterprises, improve the efficiency of enterprise management, and realize business finance integration. Finally, through the research of this paper, we hope to provide reference for other similar enterprises to apply big data for financial decision-making. Through the application of big data, higher economic benefits are achieved in procurement management, production control, capital budget, and investment decision compared with the previous ones. It is concluded that in the era of big data, massive data can be used to serve enterprise decision-making in depth, which can break the business and financial barriers, improve the efficiency and quality of decision-making, optimize the organizational structure and personnel, and enhance the prediction and early warning capability. The application of big data tools has become the key to assisting financial decision-making and enhancing enterprise value.

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Usage of Big Data Technology in Controlling

Cited by 5 publications

References 12 publications

Optimization of Ideological and Political Education Management Strategies under k-Means Algorithm in Big Data Environment

Optimization of Ideological and Political Education Management Strategies under k-Means Algorithm in Big Data Environment

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Optimization of Enterprise Financial Management and Decision‐Making Systems Based on Big Data

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